The synthetic localizer radiograph – A new CT scan planning method

Ultra-low-dose lung multidetector computed tomography in children – Approaching 0.2 millisievert

“…Authors previously published the necessity of optimizing the LR especially for paediatric patients [29,30]. While we agree that optimizations are important, some proposed methods seem to be unsuitable, as they might exceed the dose of a whole scan [31].…”

Deep Learning-based calculation of patient size and attenuation surrogates from localizer Image: Toward personalized chest CT protocol optimization

“…In addition, patient size and attenuation information extracted from the localizer image can be used to optimize the irradiation parameters according to the desired image quality and radiation dose. Knowledge of the patient's body attenuation or shape characteristics prior to spiral CT scanning is helpful in effectively optimizing spiral CT scanning to achieve automatic tunning of size-adapted exposure parameters, such as automatic tube current modulation (TCM) and automatic kVp selection [14][15][16][17]. Ichikawa et al trained a deep neural network to correlate the scout image and patient's weight with an error close to 3 kg [18].…”

“…Terashima et al [20] evaluated the effect of TH on the accuracy of DW estimates from the AP localizer and found a suitable CF based on TH with an error equal to 2.4 % in an anthropomorphic phantom study. Nowik et al [14] evaluated the radiation dose and functionality of acquiring an ultra-low-dose spiral CT scan before the main spiral CT instead of the 2D localizer within ten patients. They reported accurate size estimation and measurements of DW from the synthetic localizer compared to the routine AP or lateral 2D localizer.…”